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Criterion
Paper radar with five axes, two current and target profiles, and evidence cards beside each dimension.
Decision Making
Radar
Growth Experiment workspace showing the question, observations, and next decision.
Growth
Growth Experiment
Paper illustration of Counter Metrics with its method-specific working model.
Product Strategy
Counter Metrics
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Purposedifferent
When capabilities, maturity levels, or market positions need to be compared across several dimensions, overview is easily lost. Radar brings different characteristics into a shared picture and shows patterns faster than tables do.When growth ideas surface quickly, the temptation to build immediately instead of learning is high. A Growth Experiment frames an assumption so target group, lever, and measurement are clear before the first deployment.When a headline metric could mask side effects, it adds guardrail signals against unwanted outcomes. It connects customer value, product logic, and decision priorities. The result is captured as a counter-metric list and guardrail definitions.When two variants compete, discussions quickly decide by taste rather than effect. A/B Testing checks behavior under controlled conditions and separates real improvement from chance or expectation effects.
Complexitydifferent
MediumMediumLowHigh
Timedifferent
1-2 h1-2 Wochen30-60 min1-4 Wochen
Participantsdifferent
2-101-62-61-6
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshop + asyncAsync
Outputdifferent
Radar Map, Capability Scores, Action AreasExperiment card, Result summary, Next betCounter Metric List, Guardrail DefinitionsExperiment results, Decision log, Learning summary
Tagsno overlap
AssessmentPortfolioCapability
MarketingGrowthExperimentsLearning
MetricsMeasurementStrategyExperiments
ExperimentsGrowthAnalyticsValidation
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